Suggested rewrite: Led a cross-functional initiative that improved [business outcome] by [measurable result], demonstrating experience relevant to this role...
Principal Data Scientist, Ads
- Remote from
- USA
- Salary
- USD 268k–365,100 / yr
- Department
- Data Science & Analytics
- Employment
- Contract
- Experience
- Senior
- Published
- Apply before
- 5 Dec 2026
- Listing views
- 29
- Application actions
- 3
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About this role.
Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com.
Reddit’s Ads Data Science team is seeking a highly motivated Principal Data Scientist to drive the strategic application of advanced quantitative methods across our advertising platform to advance the intelligence powering the advertiser experience on Reddit.
In this pivotal leadership role, you will be responsible for defining and implementing the next generation of foundational data science solutions, leveraging expertise in statistics, econometrics, machine learning and/or other quantitative methods to optimize Reddit’s Ads marketplace. You will partner closely with Analytics Engineering to ensure our underlying data systems are continuously upleveled to support advanced analysis and modeling at scale. You will be a strategic partner, collaborating closely with Product, Engineering, and Business leaders to establish the long-term vision for measurement, prediction, and optimization.
As a thought leader, you will champion scientific rigor, causal inference, and economic modeling, while providing deep mentorship to the broader team. If you are passionate about applying foundational quantitative science to solve complex, high-impact business problems, join us in shaping the future of Reddit ads.
What you’ll do
- Define the future of Ads Data Science: Own the design and long-term evolution of our core Ads Data Science solutions and infrastructure, building for the next several years of continued scale, revenue growth, and relevance.
- Strategic leadership & scientific roadmap: Identify fundamental gaps and opportunities in our current systems (including platform, auction, targeting, and full-funnel relevance models). Lead the strategic design and scientific roadmap for new solutions to significantly improve Advertiser ROI, User experience, and Reddit revenue.
- Drive end-to-end impact: Take end-to-end ownership of complex problem domains such as full funnel acceleration, advertiser lifetime value (LTV), and developing advanced predictive and causal frameworks that power Reddit’s strategic investments.
- Establish scientific standards: Define and codify best practices for large-scale statistical modeling, economic analysis, causal inference, offline model evaluation, and A/B experimentation to ensure scientific rigor and trust across the Ads data science and engineering teams.
- Technical deep dive & authority: Be the undisputed domain authority for data scientists, engineers, and product managers on complex problems involving large-scale behavioral data, foundational models for strategic insights, and the economics of marketplace dynamics.
- Translate ambiguity into outcomes: Influence the design and definition of core business and performance metrics, robust measurement methodologies, and collaborate deeply with cross-org XFNs to align on strategic goals and translate insights into tangible action.
- Influence and uplevel the organization: Lead technically minded peers and mentor senior data scientists, influencing technical and statistical direction across the entire product and engineering organization, and championing innovation in ad systems through advanced quantitative techniques.
Requirements
- Demonstrated expertise in at least one of the following: ads marketplace understanding, auctioning/bidding, ads creative & format evaluation, measurement & experimentation at scale
- Master’s or Ph.D. in Economics, Statistics, Computer Science, Operations Research, or a related quantitative discipline
- For M.S. holders: 12+ years of industry experience in applied science, data science, or machine learning engineering roles
- For Ph.D. holders: 8+ years of relevant experience applied science, data science, or machine learning engineering roles
- Advanced proficiency in statistical programming (Python or R) and SQL
- Experience with statistical analysis, economic modeling, foundational machine learning and/or optimization techniques
- Strong understanding of experimental design, causal inference, or A/B testing methodologies
- Exceptional problem-solving and communication skills, with a track record of influencing product and engineering partners
- Experience working in fast-paced, ambiguous environments with cross-functional teams
- Proven experience in influencing large (500+ engineers/data scientists) organizations on technical direction, statistical rigor, and machine learning best practice
Benefits:
- Comprehensive Healthcare Benefits and Income Replacement Programs
- 401k with Employer Match
- Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
- Family Planning Support
- Gender-Affirming Care
- Mental Health & Coaching Benefits
- Flexible Vacation & Paid Volunteer Time Off
- Generous Paid Parental Leave
Pay Transparency:
This job posting may span more than one career level.
In addition to base salary, this job is eligible to receive equity in the form of restricted stock units, and depending on the position offered, it may also be eligible to receive a commission. Additionally, Reddit offers a wide range of benefits to U.S.-based employees, including medical, dental, and vision insurance, 401(k) program with employer match, generous time off for vacation, and parental leave. To learn more, please visit https://www.redditinc.com/careers/.
To provide greater transparency to candidates, we share base salary ranges for all US-based job postings regardless of state. We set standard base pay ranges for all roles based on function, level, and country location, benchmarked against similar stage growth companies. Final offer amounts are determined by multiple factors including, skills, depth of work experience and relevant licenses/credentials, and may vary from the amounts listed below.
The base salary range for this position is:
$268,000—$365,100 USD
In select roles and locations, the interviews will be recorded, transcribed and summarized by artificial intelligence (AI). You will have the opportunity to opt out of recording, transcription and summarization prior to any scheduled interviews.
During the interview, we will collect the following categories of personal information: Identifiers, Professional and Employment-Related Information, Sensory Information (audio/video recording), and any other categories of personal information you choose to share with us. We will use this information to evaluate your application for employment or an independent contractor role, as applicable. We will not sell your personal information or disclose it to any third party for their marketing purposes. We will delete any recording of your interview promptly after making a hiring decision. For more information about how we will handle your personal information, including our retention of it, please refer to our Candidate Privacy Policy for Potential Employees and Contractors.
Reddit is proud to be an equal opportunity employer, and is committed to building a workforce representative of the diverse communities we serve. Reddit is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If, due to a disability, you need an accommodation during the interview process, please let your recruiter know.
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Sample interview questions
I would begin by defining the causal estimand and identifying likely selection biases. Where feasible, I would use randomized experimentation; otherwise, I would evaluate quasi-experimental approaches such as propensity weighting, matched controls, difference-in-differences, or instrumental variables, while validating balance, assumptions, and sensitivity.
I would define a multi-objective framework with clear guardrail metrics for user experience and advertiser outcomes. I would model marketplace trade-offs, test changes through controlled experiments, and use segment-level analyses to identify where optimization improves long-term value rather than only short-term revenue.
I would first ensure labels, sampling, and temporal splits reflect production conditions. Beyond predictive metrics, I would assess calibration, stability, subgroup performance, counterfactual limitations, and the relationship between offline metrics and online business outcomes, then validate the model with a staged online experiment.
I would assess existing measurement, data quality, modeling, experimentation, and infrastructure gaps against strategic business objectives. I would prioritize foundational investments with durable leverage, define success metrics and milestones, align owners across engineering and product, and continuously revise priorities based on experimental evidence and marketplace changes.
I make uncertainty explicit, frame decisions around measurable hypotheses and trade-offs, and present evidence in terms of customer and business impact. I seek early alignment on decision criteria, communicate technical detail at the appropriate level, and create practical experiments or prototypes that reduce uncertainty quickly.
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